Rising datacentre emissions spotlight systemic AI energy demands and infrastructure gaps
Original framing: “The environmental cost of datacentres is rising. Is it time to quit AI?” — The Guardian - Environment
Scientific studies show that while AI training is energy-intensive, inference is relatively low. However, the cumulative effect of billions of queries and the lack of energy-efficient algorithms remain critical issues.
The environmental impact of AI is not an inherent flaw of the technology but a symptom of outdated infrastructure and lack of regulatory oversight.
Indigenous knowledge, historical precedents, and cross-cultural innovations all point to the possibility of sustainable AI development. By integrating green design principles, policy incentives, and community-led initiatives, it is possible to align AI with ecological and social justice goals. The future of AI depends on systemic change, not just individual action.